juliensimon/galactic-novae-schaefer
Galactic Classical Novae (Schaefer 2022) Credit: NASA/ESA/Hubble Part of a dataset collection on Hugging Face. Dataset description Schaefer's compendium of Galactic classical novae — VizieR J/MNRAS/517/6150 from Schaefer, B.E. (2022), MNRAS 517, 6150, 'The distances to Galactic classical novae'. Classical novae are thermonuclear runaways on the surface of a white dwarf accreting hydrogen from a close binary companion, producing brightening of 8-15… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/galactic-novae-schaefer.
Galactic Classical Novae (Schaefer 2022)
<div align="center"> <img src="banner.jpg" alt="Crab Nebula — Type II supernova remnant, related transient class" width="400"> <p><em>Credit: NASA/ESA/Hubble</em></p> </div>
Part of a [dataset collection](https://huggingface.co/collections/juliensimon/variable-stars-and-transients-69c792b1dd7a45812c5a9b36) on Hugging Face.
Dataset description
Schaefer's compendium of Galactic classical novae — VizieR J/MNRAS/517/6150 from Schaefer, B.E. (2022), MNRAS 517, 6150, 'The distances to Galactic classical novae'.
Classical novae are thermonuclear runaways on the surface of a white dwarf accreting hydrogen from a close binary companion, producing brightening of 8-15 magnitudes in days and a slow photometric decline lasting weeks to months. They are central to several open questions in astrophysics: as candidate progenitors of Type Ia supernovae, as contributors to the chemical enrichment of the interstellar medium with CNO-cycle isotopes, and as testbeds for binary-star evolution and degenerate-matter physics. Schaefer's paper standardized the literature compilation of two key observables for every recorded Galactic nova: V_peak (peak apparent visual magnitude at outburst) and the interstellar reddening E(B-V) along the line of sight, then combined them with multiple independent distance indicators to derive a homogeneous peak-distance-modulus catalog.
Each row in this dataset records one Galactic nova with its variable-star designation, J2000 sky position from SIMBAD, peak V magnitude and reddening from Schaefer's literature collation, and the corresponding peak distance modulus. Use this dataset alongside juliensimon/cataclysmic-variable-catalog for the broader CV parent population, juliensimon/aavso-vsx-variable-stars for ongoing time-domain photometry, juliensimon/open-supernova-catalog for the closely related thermonuclear-explosion population, and juliensimon/hot-subdwarf-stars for an alternative end state of binary-stripped stellar evolution.
This dataset is suitable for tabular classification tasks.
Schema
Quick stats
- 402 Galactic classical novae with literature-compiled photometry and reddening
- Homogeneous peak-magnitude catalog spanning over a century of recorded outbursts
- Peak apparent magnitudes (V_peak) span -0.5 to 17.5 mag
- Interstellar reddening E(B-V) ranges from 0.02 to 4.00 mag — many novae lie behind heavy Galactic dust
- Distance moduli at peak: 5.9 to 20.9 mag (heliocentric distances ~0.3 to ~30 kpc)
Usage
from datasets import load_dataset
ds = load_dataset("juliensimon/galactic-novae-schaefer", split="train")
df = ds.to_pandas()from datasets import load_dataset
import matplotlib.pyplot as plt
import numpy as np
df = load_dataset("juliensimon/galactic-novae-schaefer", split="train").to_pandas()
# Reddening vs distance modulus — heavy dust traces Galactic plane novae
mask = df["ebv"].notna() & df["distance_modulus_peak"].notna()
fig, ax = plt.subplots(figsize=(8, 6))
ax.scatter(df.loc[mask, "distance_modulus_peak"], df.loc[mask, "ebv"],
s=30, alpha=0.7)
ax.set_xlabel("Distance modulus at peak (mag)")
ax.set_ylabel("E(B-V) reddening (mag)")
ax.set_title("Galactic novae: reddening grows with distance through the disk")
plt.tight_layout()
plt.show()
# Derive heliocentric distance from distance modulus, correcting for extinction
dist_pc = 10 ** ((df["distance_modulus_peak"] - 3.1 * df["ebv"] + 5) / 5)
print(f"Median heliocentric distance: {np.nanmedian(dist_pc) / 1000:.1f} kpc")Data source
https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/517/6150
Related datasets
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About the author
Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.
Citation
@dataset{galactic_novae_schaefer,
title = {Galactic Classical Novae (Schaefer 2022)},
author = {Simon, Julien},
year = {2026},
url = {https://huggingface.co/datasets/juliensimon/galactic-novae-schaefer},
publisher = {Hugging Face},
note = {Derived from CDS Archive, Centre de Données astronomiques de Strasbourg, https://cdsarc.cds.unistra.fr/viz-bin/cat/J/MNRAS/517/6150}
}